Paper list

• 1729 Seeing isn't Believing: Towards More Robust Adversarial Attack Against Real World Object Detectors Autonomous Vehicle Object detection manualSet YOLO YOLOv3 Faster R-CNN
• 1730 MeshAdv: Adversarial Meshes for Visual Recognition Autonomous Vehicle Object detection manualSet DenseNet Inception-v3 YOLOv3 3D meshes Adversarial mesh
• 1735 Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors Autonomous Vehicle Object detection manualSet YOLOv2 YOLOv3 YOLO Faster R-CNN Physical-World Camera
• 1737 CCA: Exploring the Possibility of Contextual Camouflage Attack on Object Detection Autonomous Vehicle Object detection manualSet YOLOv3 Mask-RCNN Grad-CAM Camera
• 1738 SADA: Semantic Adversarial Diagnostic Attacks for Autonomous Applications Autonomous Vehicle Object detection manualSet EndToEnd driving YOLOv3 YOLO CARLA CARLA driving simulator wWather setting Sim4CV
• 1740 Daedalus: Breaking Non-Maximum Suppression in Object Detection via Adversarial Examples Autonomous Vehicle Object detection manualSet YOLO YOLOv3 RetinaNet-ResNet-50 SSD
• 1743 Fooling thermal infrared pedestrian detectors in real world using small bulbs Autonomous Vehicle Object detection manualSet Thermal infrared detection systems YOLOv3 FLIR ADAS Physical-World
• 1747 Fooling Detection Alone is Not Enough: Adversarial Attack against Multiple Object Tracking Autonomous Vehicle Object tracking manualSet YOLOv3
• 1766 Adversarial Attacks on Camera-LiDAR Models for 3D Car Detection Autonomous Vehicle manualSet Camera LiDAR MSF KITTI YOLOv3 EPNet PointRCNN Module-level Virtual evaluation